code: def test_var_aggregation():
      x = torch.randn(6, 16)
      index = torch.tensor([0, 0, 1, 1, 1, 2])
  
      var_aggr = VarAggregation()
      out = var_aggr(x, index)
  
      mean_aggr = MeanAggregation()
      expected = mean_aggr(
          (x - mean_aggr(x, index)[index]).pow(2), index
      )
      assert torch.allclose(out, expected, atol=1e-6)
  
file_path: pytorch_geometric/test/nn/aggr/test_basic.py
imports: import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric.nn import MaxAggregation, MeanAggregation, MinAggregation, MulAggregation, PowerMeanAggregation, SoftmaxAggregation, StdAggregation, SumAggregation, VarAggregation
label_desc: Use image node_id 3 for calling a global function with example usage: test_var_aggregation() without return types